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Record W2575615576 · doi:10.1177/1367493516689167

Longitudinal patterns of early development in Canadian late preterm infants

2017· article· en· W2575615576 on OpenAlexaffabout
Karen Benzies, Joyce Magill‐Evans, Marilyn Ballantyne, Jana Kurilova

Bibliographic record

VenueJournal of Child Health Care · 2017
Typearticle
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalUniversity of AlbertaUniversity of Calgary
Fundersnot available
KeywordsLongitudinal studyMedicineGross motor skillPediatricsReferralNormativePopulationCohortChild developmentCohort studyFull TermGestational ageProspective cohort studyDemographyMotor skillPregnancyPsychiatrySurgery

Abstract

fetched live from OpenAlex

This prospective, longitudinal cohort study examined longitudinal patterns of early development in Canadian children born late preterm. A convenience sample of 82 mothers and their healthy, singleton, late preterm children participated. Mothers completed the Ages and Stages Questionnaires at 4, 8, and 18 months corrected age. Concerns were most commonly reported in the communication and gross motor domains, especially early in development. The proportion of children scoring below the referral cut-off in at least one domain at 4, 8, and 18 months was, respectively, 25.6, 25.6, and 14.6%. Only two children (2.4%) scored below referral cut-off in at least one domain at all three time points. At ages four and eight months, the late preterm sample had significantly lower communication and gross motor scores than the Ages and Stages Questionnaires normative sample. At age four months, there was also a significant difference on the fine motor domain. There were no significant differences at age 18 months. Healthy late preterm children appear to catch up to population norms by age 18 months corrected age. Longer term studies are needed to further clarify early indicators of delay in late preterm children and identity those who require close developmental monitoring.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.096
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.309
Teacher spread0.290 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations15
Published2017
Admission routes2
Has abstractyes

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